archd3sai/News-Articles-Recommendation

Objective of the project is to build a hybrid-filtering personalized news articles recommendation system which can suggest articles from popular news service providers based on reading history of twitter users who share similar interests (Collaborative filtering) and content similarity of the article and user’s tweets (Content-based filtering).

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Emerging

This system helps online news providers personalize content for their readers. By analyzing a user's Twitter activity and interests, it recommends news articles from popular providers that are most relevant to them. It takes a Twitter handle as input and outputs a list of personalized news article recommendations, aiming to increase reader engagement and retention.

No commits in the last 6 months.

Use this if you are an online news provider looking to offer tailored news feeds to your audience based on their public social media interactions.

Not ideal if your target audience does not actively use Twitter or if you prefer not to leverage public social media data for personalization.

news-personalization audience-engagement content-recommendation social-media-marketing digital-publishing
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 17 / 25

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Stars

41

Forks

11

Language

Jupyter Notebook

License

MIT

Last pushed

Mar 14, 2020

Commits (30d)

0

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